crowston

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Conference Paper
Dalgali, A., & Crowston, K.. (2020). Algorithmic Journalism and Its Impacts on Work. In Computation + Journalism Symposium. Presented at the Computation + Journalism Symposium . Retrieved de https://cpb-us-w2.wpmucdn.com/express.northeastern.edu/dist/d/53/files/2020/02/CJ_2020_paper_26.pdf
PDF icon CJ_2020_paper_26.pdf (1.24 MB)
Conference Proceedings
Crowston, K., & Rezgui, A.. (2020). Effects of stigmergic and explicit coordination on Wikipedia article quality. In Hawai'i International Conference on System Science. https://doi.org/10.24251/HICSS.2020.287
PDF icon Stigmergy_in_Wikipedia_HICSS_2020.pdf (654.41 KB)
Dalgali, A., & Crowston, K.. (2020). Factors Influencing Approval of Wikipedia Bots. In Hawai'i International Conference on System Science. https://doi.org/10.24251/HICSS.2020.018
PDF icon HICSS_WikipediaPaper_3.9.new kc (2).pdf (473.63 KB)
Harandi, M., Crowston, K., Jackson, C., & Østerlund, C.. (2020). The Genie in the Bottle: Different Stakeholders, Different Interpretations of Machine Learning. In Hawai'i International Conference on System Science. https://doi.org/10.24251/HICSS.2020.719
PDF icon Social_Construction_of_ML_in_GS_HICCS2020.pdf (124.3 KB)
Crowston, K., & Bolici, F.. (2020). Impacts of the Use of Machine Learning on Work Design. In 8th International Conference on Human-Agent Interaction. https://doi.org/10.1145/3406499.3415070
PDF icon Impacts_of_ML_for_HAI_2020.pdf (453.59 KB)
Journal Article
Crowston, K., Østerlund, C., Lee, T. Kyoung, Jackson, C. B., Harandi, M., Allen, S., et al.. (2020). Knowledge Tracing to Model Learning in Online Citizen Science Projects. Ieee Transactions On Learning Technologies, 13, 123-134. https://doi.org/10.1109/TLT.2019.2936480
PDF icon transaction paper final figures in text.pdf (1.39 MB)
Conference Paper
Crowston, K. (2020). Lessons for Supporting Data Science from the Everyday Automation Experience of Spell-Checkers. In Automation Experience across Domains (AutomationXP20), CHI'20 Workshop, 26 April 2020, Virtual. Presented at the Automation Experience across Domains (AutomationXP20), CHI'20 Workshop, 26 April 2020, Virtual, Virtual workshop.
PDF icon Everyday_automation camera ready.pdf (421.84 KB)
Journal Article
Saltz, J., Crowston, K., Heckman, R., & Hegde, Y.. (2020). MIDST: An enhanced development environment that improves the maintainability of a data science analysis. International Journal Of Information Systems And Project Management, 8(3). https://doi.org/10.12821/ijispm080301
Jackson, C. B., Østerlund, C., Harandi, M., Crowston, K., & Trouille, L.. (2020). Shifting forms of Engagement: Volunteer Learning in Online Citizen Science. Proceedings Of The Acm On Human-Computer Interaction, (CSCW), 36. https://doi.org/10.1145/3392841
PDF icon 3392841.pdf (1.13 MB)
Jackson, C., Østerlund, C., Crowston, K., Harandi, M., Allen, S., Bahaadini, S., et al.. (2020). Teaching Citizen Scientists to Categorize Glitches using Machine-Learning-Guided Training. Computers In Human Behavior, 105, 106198. https://doi.org/10.1016/j.chb.2019.106198
PDF icon MLGT-preprint.pdf (2.43 MB)
Crowston, K., Mitchell, E. Michelle, & Østerlund, C.. (2019). Coordinating Advanced Crowd Work: Extending Citizen Science. Citizen Science: Theory And Practice, 4, 1–12. https://doi.org/10.5334/cstp.166
Conference Proceedings
You, S., Crowston, K., Saltz, J., & Hegde, Y.. (2019). Coordination in OSS 2.0: ANT Approach. In Proceedings of the 52nd Hawai'i International Conference on System Sciences (HICSS-52). https://doi.org/10.24251/HICSS.2019.120
PDF icon hicss52a-sub2136-cam-i8-2.pdf (202.19 KB)
Conference Proceedings
Saltz, J., Heckman, R., Crowston, K., You, S., & Hegde, Y.. (2019). Helping data science students develop task modularity. In Proceedings of the 52nd Hawai'i International Conference on System Sciences (HICSS-52). https://doi.org/10.24251/HICSS.2019.134
PDF icon modularity-HICSS-final-afterReview.pdf (242.49 KB)
Conference Proceedings
Crowston, K., & Bolici, F.. (2019). Impacts of machine learning on work. In Proceedings of the 52nd Hawai'i International Conference on System Sciences (HICSS-52). https://doi.org/10.24251/HICSS.2019.719
PDF icon Impacts_of_machine_learning_on_work__revision_.pdf (300.76 KB)

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